PT Journal
AU Sergio Escalera
   Xavier Baro
   Jordi Vitria
   Petia Radeva
   Bogdan Raducanu
TI Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction
SO Sensors
JI SENS
PY 2012
BP 1702
EP 1719
VL 12
IS 2
DI 10.3390/s120201702
AB IF=1.77 (2010)Social interactions are a very important component in peopleís lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the  characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Timesí Blogging Heads opinion blog.The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The linksí weights are a measure of the ìinfluenceî a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.
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